Abstract: Aspects of a data environment, such as the cloning, hibernation, and recovery of databases, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform actions such as recovery, hibernation, resumption from hibernation, or backup or cloning. Tasks of the workflow can cause certain jobs to be performed by host managers in the data environment to affect calls made to the control environment.

Abstract: A method may include a obtaining a first data model instance comprising an identifier string and. a set of attributes associated with a set of attribute name strings. The method may include obtaining an ontology graph that includes a first label, a second label, and an association between them. The method may include using a prediction model to select the first label based on the first data model instance and determining the second label based on the relationship. The method may include determining a selected set of labels that includes the first label and the second label to associate with the first data model instance. The method may include associating the selected set of labels with the first data model instance in a dataset that includes a plurality of records, where each record is associated with a different data model instance.

Abstract: Aspects of a data environment, such as the cloning, hibernation, and recovery of databases, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform actions such as recovery, hibernation, resumption from hibernation, or backup or cloning. Tasks of the workflow can cause certain jobs to be performed by host managers in the data environment to affect calls made to the control environment.

Abstract: A method may include a obtaining a first data model instance comprising an identifier string and a set of attributes associated with a set of attribute name strings. The method may include obtaining an ontology graph that includes a first label, a second label, and an association between them. The method may include using a prediction model to select the first label based on the first data model instance and determining the second label based on the relationship. The method may include determining a selected set of labels that includes the first label and the second label to associate with the first data model instance. The method may include associating the selected set of labels with the first data model instance in a dataset that includes a plurality of records, where each record is associated with a different data model instance.

Abstract: Aspects of a data environment, such as various capacities of data stores and instances, can be managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to obtain performance information. The information is analyzed, using algorithms such as trending and extrapolation algorithms, to determine any recommended scaling of resources in the data environment. The scaling can be performed automatically, or as authorized by a customer. A workflow can be instantiated that includes tasks necessary to perform the scaling. The scaling of storage capacity can be performed without affecting the availability of the data store.

Abstract: Aspects of a data environment, such as the cloning, hibernation, and recovery of databases, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform actions such as recovery, hibernation, resumption from hibernation, or backup or cloning. Tasks of the workflow can cause certain jobs to be performed by host managers in the data environment to affect calls made to the control environment.

Abstract: Aspects of a data environment, such as various capacities of data stores and instances, can be managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to obtain performance information. The information is analyzed, using algorithms such as trending and extrapolation algorithms, to determine any recommended scaling of resources in the data environment. The scaling can be performed automatically, or as authorized by a customer. A workflow can be instantiated that includes tasks necessary to perform the scaling. The scaling of storage capacity can be performed without affecting the availability of the data store.

Abstract: A method may include a obtaining a first data model instance comprising an identifier string and. a set of attributes associated with a set of attribute name strings. The method may include obtaining an ontology graph that includes a first label, a second label, and an association between them. The method may include using a prediction model to select the first label based on the first data model instance and determining the second label based on the relationship. The method may include determining a selected set of labels that includes the first label and the second label to associate with the first data model instance. The method may include associating the selected set of labels with the first data model instance in a dataset that includes a plurality of records, where each record is associated with a different data model instance.

Abstract: Aspects of a data environment, such as various capacities of data stores and instances, can be managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to obtain performance information. The information is analyzed, using algorithms such as trending and extrapolation algorithms, to determine any recommended scaling of resources in the data environment. The scaling can be performed automatically, or as authorized by a customer. A workflow can be instantiated that includes tasks necessary to perform the scaling. The scaling of storage capacity can be performed without affecting the availability of the data store.

Abstract: Aspects of a data environment, such as various capacities of data stores and instances, can be managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to obtain performance information. The information is analyzed, using algorithms such as trending and extrapolation algorithms, to determine any recommended scaling of resources in the data environment. The scaling can be performed automatically, or as authorized by a customer. A workflow can be instantiated that includes tasks necessary to perform the scaling. The scaling of storage capacity can be performed without affecting the availability of the data store.

Abstract: Aspects of a data environment, such as various capacities of data stores and instances, can be managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to obtain performance information. The information is analyzed, using algorithms such as trending and extrapolation algorithms, to determine any recommended scaling of resources in the data environment. The scaling can be performed automatically, or as authorized by a customer. A workflow can be instantiated that includes tasks necessary to perform the scaling. The scaling of storage capacity can be performed without affecting the availability of the data store.

Abstract: Aspects of a data environment, such as the cloning, hibernation, and recovery of databases, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform actions such as recovery, hibernation, resumption from hibernation, or backup or cloning. Tasks of the workflow can cause certain jobs to be performed by host managers in the data environment to affect calls made to the control environment.

Abstract: Aspects of a data environment, such as the cloning, hibernation, and recovery of databases, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform actions such as recovery, hibernation, resumption from hibernation, or backup or cloning. Tasks of the workflow can cause certain jobs to be performed by host managers in the data environment to affect calls made to the control environment.

Abstract: Aspects of a data environment, such as the cloning, hibernation, and recovery of databases, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform actions such as recovery, hibernation, resumption from hibernation, or backup or cloning. Tasks of the workflow can cause certain jobs to be performed by host managers in the data environment to affect calls made to the control environment.

Abstract: Aspects of a data environment, such as various capacities of data stores and instances, can be managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to obtain performance information. The information is analyzed, using algorithms such as trending and extrapolation algorithms, to determine any recommended scaling of resources in the data environment. The scaling can be performed automatically, or as authorized by a customer. A workflow can be instantiated that includes tasks necessary to perform the scaling. The scaling of storage capacity can be performed without affecting the availability of the data store.

Abstract: Aspects of a data environment, such as the cloning, hibernation, and recovery of databases, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform actions such as recovery, hibernation, resumption from hibernation, or backup or cloning. Tasks of the workflow can cause certain jobs to be performed by host managers in the data environment to effect calls made to the control environment.

Abstract: Aspects of a data environment, such as the monitoring, backup, and recovery of data stores and instances, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform a recovery action. Tasks of the workflow can instantiate a new data instance and, using an identifier for the original data instance, access a snapshot for the data instance and copy the data to the new instance. Log files also can be accessed and applied to the new data instance to cause the new instance to represent the state of the original data instance at a particular point in time.

Abstract: Aspects of a data environment, such as various capacities of data stores and instances, can be managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to obtain performance information. The information is analyzed, using algorithms such as trending and extrapolation algorithms, to determine any recommended scaling of resources in the data environment. The scaling can be performed automatically, or as authorized by a customer. A workflow can be instantiated that includes tasks necessary to perform the scaling. The scaling of storage capacity can be performed without affecting the availability of the data store.

Abstract: Aspects of a data environment, such as the monitoring, backup, and recovery of data stores and instances, are managed using a separate control environment. A monitoring component of the control environment can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events for a data instance in the data environment. A workflow can be instantiated that includes tasks necessary to perform a recovery action. Tasks of the workflow can instantiate a new data instance and, using an identifier for the original data instance, access a snapshot for the data instance and copy the data to the new instance. Log files also can be accessed and applied to the new data instance to cause the new instance to represent the state of the original data instance at a particular point in time.